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Copernicus Land Monitoring Service has recently launched a group of high-resolution snow cover products which are derived from Sentinel-1 and Sentinel-2 constellations. High- Resolution Snow and Ice Monitoring (HRSI) products include Fractional Snow Cover (FSC) from the Sentinel-2 constellation and Wet and Dry Snow (WDS) covering Europe and SAR Wet Snow (SWS) products for selected mountain regions derived from the Sentinel-1 constellation. The FSC and WDS products have gaps in the snow cover data due to cloud presence and the SWS product provides only information on the melting snow extent, but dry snow areas and snow-free areas cannot be discriminated by means of SAR data. In the same portfolio, we provide the daily cumulative Gap-filled Fractional Snow Cover (GFSC) product, which is a fusion of those three products. In this product, we gap-fill the FSC product using the wet snow presence detected by the SWS in the spatial domain. In the temporal domain, all recent data in the last 7 days are used for gap-filling by temporal composition. The product aims to have a complete snow cover map of Europe. The quality of the product is assessed using in-situ data and gap simulation, for the period of 09.2017 - 08.2018 for mountain ranges in the Pyrenees, Alps, Scandinavia , East Turkey and Corsica, covered by 34 Sentinel-2 tiles. In-situ snow depth information is converted to binary snow cover information using a snow depth threshold. For the gap simulation method, as first step, FSC products with observed snow information are selected. Then, an artificial cloud mask is overlaid on these products, and the gap-filling method is run to generate GFSC products. The resulting GFSC products are compared with the corresponding observed FSC products, considering them as reference data. This comparison shows the agreement between the FSC product and the gap-filling methods. For both comparison methods, FSC values in GFSC and FSC products are converted to binary snow cover information using an FSC threshold. Resulting binary snow cover information is used in contingency tables and performance metrics are calculated for the product and for different gap-filling methods. We have found that the gap-filling provides 5 times more pixels with snow cover information and the quality is fairly good. The comparison with in-situ data shows an accuracy over 88% in temporal gap-filling and precision over 87% in spatial gap-filling. The comparison of the gap simulated GFSC and the FSC products shows an accuracy over 97% in temporal gap-filling and precision over 83% in spatial gap-filling. Temporal gap-filling performance is consistent throughout the seasons, although it is less accurate in the accumulation season for the spatial gap-filling, which is expected as the wet snow algorithm is developed for the melting season conditions. The assessment shows that the methods are working well and 7 days old FSC, WDS and SWS data are still valid to fill the gaps in the data.

The limited availability of Synthetic Aperture Radar (SAR) data over glaciers and ice sheets in the past, which formed a major obstacle for obtaining consistent climate data records, has been overcome by the Copernicus Sentinel-1 (S-1) mission, launched in 2014. S-1 SAR data in Greenland, Antarctica and other polar regions have since been regularly acquired every 6 to 12 days, allowing for the operational monitoring and time series analysis of key climate variables at a high spatial and temporal resolution. Exploiting the extensive archive of S-1 acquisitions, we have developed algorithms for retrieving dense time series of glacier and ice sheet velocities, ice discharge and surface melt processes, facilitated by the ESA Climate Change Initiative (ESA CCI), ESA Polar Science Cluster (ESA POLAR+) and EU Copernicus Climate Change Service (C3S) programs. In order to improve existing ice velocity products, we have implemented an InSAR processing line for generation of high-resolution velocity fields from crossing orbits and included a tide correction module to the offset-tracking processing line which accounts for the vertical motion of floating ice shelves and ice tongues due to ocean tides and pressure differences. We present synergistic InSAR and offset tracking ice velocity products, derived from repeat pass S-1 Interferometric Wide (IW mode) swath data, for the Greenland Ice Sheet and report on the performance of the products using in-situ GPS data. Additionally, we show velocity variations of major outlet glaciers in Greenland and Antarctica and other polar ice bodies. The generated ice velocity maps, complemented with ice thickness and other Earth observation datasets, form the basis for deriving ice flow and discharge fluctuations and trends at sub-monthly to multi-annual time scales. To evaluate snowmelt dynamics in Greenland and Antarctica, we have also developed an algorithm for generating maps of snowmelt extent based on multitemporal S-1 SAR and Advanced Scatterometer (ASCAT) data. The dense backscatter time series yields a unique temporal signature that is used to identify the different stages of the melt/freeze cycle and to estimate the melting intensity of the surface snowpack. The high-resolution melt maps form the main input for deriving value-added products on annual melt onset, ending and duration. Intercomparisons with in-situ weather station data and melt products derived from regional climate models (RCMs) and passive microwave radiometers confirm the ability of the algorithm to detect short-lived and longer melt events. Our results demonstrate the excellent capability of the S-1 mission in combination with other sensors for comprehensive monitoring of key climate variables on glaciers and ice sheets, providing essential input for various applications such as ice dynamic and climate modelling.

Seasonal snow is one of the terrestrial essential climate variables specified by the Global Climate Observing System (GCOS). With a coverage of about 45 to 50 Mio. km² of the global land area during the main winter season in the past decades, seasonal snow is the largest component of the cryosphere having a major impact on different processes of the Earth’s system.Different medium resolution optical satellite data have been exploited in the past few years to monitor the seasonal snow extent on local to global scale. Most of these satellite-based products provide information on the snow viewable from space, i.e. in forested areas the snow viewable on top of the forest canopy, and many of these products provide only binary classification on snow, i.e. a pixel is either snow covered or snow free.In the frame of the ESA Climate Change Initiative Extension (CCI+) Snow, a new climate data record (CDR) of daily global snow cover fraction maps with about 1 km pixel spacing was generated from Terra MODIS and Sentinel-3 SLSTR data for the period 2000 – 2020. The daily products of this CDR provide the fraction of snow covered area per pixel in percentage not only for all land areas, but differentiate in forested areas two thematic snow information, the snow cover fraction viewable from above, and the snow cover fraction on the ground. The retrieval method assures that the classified snow cover fraction on ground and the viewable snow cover fraction information are consistent for all observed land areas, allowing the usage of the data sets in different applications. Each daily product contains the unbiased root mean square error per observed pixel as uncertainty estimation. The CDR will be publicly released via the ESA Open Data Portal soon.Based on the new CDR, the variability of the seasonal snow in the past 20 years is analysed, investigating in detail interannual, seasonal and monthly trends on global and hemispheric scales. The maximum global snow cover in the past 20 years shows overall a negative trend, although the derived interannual variations reach up to 5 Mio. km². The analysis of the seasonal snow extent indicates no significant trend of the maximum snow cover during the main winter season on the Northern Hemisphere (January – March) in the past 20 years. But during the onset and the melting seasons of the Northern Hemisphere, all the trends of the maximum snow area are negative, with the most negative signal in May.We will present the method used for the generation of the new snow cover fraction CDR from MODIS and SLSTR data and discuss the results of the spatial and temporal analyses of the 20-years time series of global daily snow cover fraction products, including also analyses of the variations in the timing and duration of the snow season for selected regions in the context of the changing climate.

The Sentinel-1 acquisition planning for polar regions provides almost uninterrupted observations of the Greenland Ice Sheet margin, key regions in Antarctica and other polar ice masses. The satellite constellation has thereby changed the landscape for satellite Earth observation (EO) in the polar regions, providing excellent opportunities for operational monitoring of key climate variables including ice velocity and glacier discharge. Based on Sentinel-1 SAR imagery, an archive of ice velocity maps covering the polar regions has been generated, encompassing the entire mission duration. The ice velocity maps, complemented with ice thickness and other EO datasets, form the basis for deriving ice flow, discharge fluctuations and trends at sub-monthly to multi-annual time scales, providing key input for ice dynamic and climate modelling. Our results underscore the value of long-term comprehensive monitoring of the polar ice masses, which is vital to gain insight for predicting their response to ongoing climate and ocean warming.

Recent years have seen major advancements in satellite Earth observation of polar land ice. Among the most notable are the developments enabled by the Copernicus Sentinel program, including the Sentinel-1 SAR mission. The Sentinel-1 constellation, with its dedicated polar acquisition scheme, has provided the opportunity to derive ice flow velocity of the Greenland and Antarctic ice sheets at an unprecedented scale and temporal sampling. A continuous observational record of the ice sheet margins since October 2014, augmented by dedicated ice sheet wide mapping campaigns, enabled the operational monitoring of key climate variables like ice velocity and glacier discharge. In 2019 additional tracks have been added to the regular acquisition scheme, covering the slow-moving interior of the Greenland Ice Sheet, opening up new opportunities for interferometric applications and permitting to derive monthly ice sheet wide velocity maps. Based on repeat pass Sentinel-1 SAR data, acquired in Interferometric Wide (IW) swath mode, we have generated a dense archive of ice velocity maps covering the polar regions and encompassing the entire mission duration, now spanning well over 5 years. Including the latest observational data, we present ice velocity maps of Greenland, Antarctica and other major ice caps, focusing on time series of ice flow fluctuations of major outlet glaciers. The ice velocity maps, complemented by high resolution DEMs and ice thickness data, form the basis for studying ice dynamics and discharge fluctuations and trends at sub-monthly to multi-annual time scales. Our results underscore the value of long-term comprehensive monitoring of the polar ice masses, which is vital for to gain insight for predicting their response to ongoing climate warming.This poster highlights some of the main achievements and latest developments of 5 years of Sentinel-1 ice flow mapping in the Polar regions facilitated by the ESA Climate Change Initiative (CCI), EU Copernicus Climate Change Service (C3S) and Austrian Space Applications Programme (ASAP).

The Sentinel satellite constellation series, developed and operated by the European Space Agency, represents the dedicated space component of the European Copernicus program, committed to long-term operational services in environment, climate and security. We developed, tested and evaluated an algorithm for generating maps of snowmelt area from C-band synthetic aperture radar (SAR) data of the Sentinel-1 mission. For snowmelt classification, a change detection method is applied, using multitemporal dual-polarized SAR data acquired in Interferometric Wide swath (IW) mode, the basic operation mode over land surfaces. Of particular benefit for wet snow retrievals are the high instrument stability, the high spatial resolution across the 250 km wide swath, and the short revisit time. In order to study the impact of polarization, we generated maps of melting snow using data of the VV-polarized channel, the VH-polarized channel and a combined VV- and VH-based channel using a weighting function that accounts for effects of the local incidence angle. Comparisons are performed with snow maps derived from Landsat images over study areas in the Alps and in Iceland. The pixel-by-pixel comparisons show good agreement between the snow products of the two sensors, with the best performance for retrievals based on the combined (VV and VH) channel and a minor decline for the VH-based product. The VV-based snowmelt extent product shows a drop-off in quality over areas with steep terrain because of the decreasing backscatter contrast of snow-covered versus snow-free surfaces on fore-slopes. The investigations demonstrate the excellent capability of the Sentinel-1 mission for operational monitoring of snowmelt areas.

We use repeat-pass SAR data to produce detailed maps of surface motion covering the glaciers draining into the former Larsen B ice shelf, Antarctic Peninsula, for different epochs between 1995 and 2013. We combine the velocity maps with estimates of ice thickness to analyze fluctuations of ice discharge. The collapse of the central and northern sections of the ice shelf in 2002 led to a near-immediate acceleration of tributary glaciers as well as of the remnant ice shelf in Scar Inlet. Velocities of the glaciers discharging directly into the ocean remain to date well above the velocities of the pre-collapse period. The response of individual glaciers differs and velocities show significant temporal fluctuations, implying major variations in ice discharge and mass balance as well. Due to reduced velocity and ice thickness the ice discharge of Crane Glacier decreased from 5.02 Gt a−1 in 2007 to 1.72 Gt a−1 in 2013, whereas Hektoria and Green glaciers continue to show large temporal fluctuations in response to successive stages of frontal retreat. The velocity on Scar Inlet ice shelf increased two- to three fold since 1995, with the largest increase in the first years after the break-up of the main section of Larsen B. Flask and Leppard glaciers, the largest tributaries to Scar Inlet ice shelf, accelerated. In 2013 their discharge was 38%, respectively 45%, higher than in 1995.